docstr: Validate the output dimensions of a MelResNet block.
docstr_tok: ["Validate","the","output","dimensions","of","a","MelResNet","block","."]
code: def test_waveform(self):
      """Validate the output dimensions of a MelResNet block."""
  
      n_batch = 2
      n_time = 200
      n_freq = 100
      n_output = 128
      n_res_block = 10
      n_hidden = 128
      kernel_size = 5
  
      model = MelResNet(
          n_res_block, n_freq, n_hidden, n_output, kernel_size
      )
  
      x = torch.rand(n_batch, n_freq, n_time)
      out = model(x)
  
      assert out.size() == (n_batch, n_output, n_time - kernel_size + 1)
  
imports: import itertools
  from collections import namedtuple
  import torch
  from parameterized import parameterized
  from torchaudio.models import ConvTasNet, DeepSpeech, Wav2Letter, WaveRNN
  from torchaudio.models.wavernn import MelResNet, UpsampleNetwork
  from torchaudio_unittest import common_utils
  from torchaudio_unittest.common_utils import torch_script
label_desc: Use image node_id 1 for calling the TestMelResNet obj's underlying member method code with example usage: obj.test_waveform() without return types